Anto01 faa7779a43 feat: Add L-BFGS gradient optimizer for surrogate polish phase ...

Implements gradient-based optimization exploiting MLP surrogate differentiability.
Achieves 100-1000x faster convergence than derivative-free methods (TPE, CMA-ES).

New files:
- optimization_engine/gradient_optimizer.py: GradientOptimizer class with L-BFGS/Adam/SGD
- studies/M1_Mirror/m1_mirror_adaptive_V14/run_lbfgs_polish.py: Per-study runner

Updated docs:
- SYS_14_NEURAL_ACCELERATION.md: Full L-BFGS section (v2.4)
- 01_CHEATSHEET.md: Quick reference for L-BFGS usage
- atomizer_fast_solver_technologies.md: Architecture context

Usage: python -m optimization_engine.gradient_optimizer studies/my_study --n-starts 20

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2025-12-28 16:36:18 -05:00

..

commands

feat: Implement Agentic Architecture for robust session workflows

2025-12-07 14:52:25 -05:00

skills

feat: Add L-BFGS gradient optimizer for surrogate polish phase

2025-12-28 16:36:18 -05:00

ATOMIZER_CONTEXT.md

feat: Add TrialManager and DashboardDB for unified trial management

2025-12-28 12:20:19 -05:00

settings.local.json

feat: Dashboard improvements and configuration updates

2025-12-20 13:47:05 -05:00